The direction of research in IFD points towards finding ways to transfer the success on lab datasets to successful applications on industry datasets [1]}, [2]}.
Both transfer learning and weak supervision can create the opportunity to implement successful algorithms on new datasets without requiring an expensive labelling process.
Inspired by recent innovations in TLP and NLS, TLS present a third, yet unutilized direction to integrate the annotations present in CM datasets as labels, learning directly from technical language.
